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---
license: apache-2.0
base_model: barghavani/Cheese_xray
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: Cheese_xray
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: chest-xray-classification
type: chest-xray-classification
config: full
split: test
args: full
metrics:
- name: Accuracy
type: accuracy
value: 0.8883161512027491
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Cheese_xray
This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on the chest-xray-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2827
- Accuracy: 0.8883
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3993 | 0.99 | 63 | 0.4364 | 0.7165 |
| 0.3454 | 1.99 | 127 | 0.3947 | 0.7680 |
| 0.3327 | 3.0 | 191 | 0.3582 | 0.8591 |
| 0.3329 | 4.0 | 255 | 0.3371 | 0.8746 |
| 0.2992 | 4.99 | 318 | 0.3449 | 0.8643 |
| 0.3289 | 5.99 | 382 | 0.3172 | 0.8832 |
| 0.3309 | 7.0 | 446 | 0.2956 | 0.8935 |
| 0.2875 | 8.0 | 510 | 0.2911 | 0.8883 |
| 0.2764 | 8.99 | 573 | 0.2884 | 0.9124 |
| 0.265 | 9.88 | 630 | 0.2827 | 0.8883 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|